E ect of MPI tasks location on cluster throughput using NAS

Abstract

In this work the Numerical Aerodynamic Simulation (NAS) benchmarks have been executed in a systematic way on two

clusters of rather different architectures and CPUs, to identify dependencies between MPI tasks mapping and the speedup

or resource occupation. To this respect, series of experiments with the NAS kernels have been designed to take into account

the context complexity when running scientific applications on HPC environments (CPU, I/O or memory-bound, execution

time, degree of parallelism, dedicated computational resources, strong- and weak-scaling behaviour, to cite some). This

context includes scheduling decisions, which have a great influence on the performance of the applications, making

difficult to achieve an optimal exploitation with cost-effective strategies of the HPC resources. An analysis on how task

grouping strategies under various cluster setups drive the execution time of jobs and the infrastructure throughput is

provided. As a result, criteria for cluster setup arise linked to maximize performance of individual jobs, total cluster

throughput or achieving better scheduling. To this respect, a criterion for execution decisions is suggested. This work is

expected to be of interest on the design of scheduling policies and useful to HPC administrators